Category: 3 SPL Desktop Analysis

Horizontal merging is also a common Excel problem encountered in work, and it is also quite troublesome to do in Excel, and many people do not know how to do it. For example, how to do one-on-one, how to do one-to-many, how to do with different number of rows, and how to do with multiple merge conditions. This article provides detailed solutions for these scenarios. And the method here is definitely the most efficient one that you have found. Let’s skip the formalities and get straight to business. Firstly, we need to use a tool called esProc SPL, which is

In the workplace, it is often necessary to summarize and sum data from multiple tables. Do you know how to do this? Today, we will teach you an efficient data aggregation method for several common situations, which can be completed in one minute. Type 1: Data comes from multiple Excel files and is summarized into a new Excel file. Type 2: Data comes from multiple sheets in the same Excel, insert a summary sheet. Firstly, we need to use a tool called esProc SPL, which is a software specifically designed to handle structured table data. It has powerful computing capabilities

How to merge multiple Excel files? How to merge Excel with the same type? What if there is duplicate data during the merge? How to summarize data from multiple files? I believe many colleagues will encounter similar problems in their work, and a large number of them will be at a loss when facing these problems. There are too many tables, copying and pasting is not advisable, PQ is not enough, and Python is too cumbersome. Is there a simpler and more automated way? Today, we will introduce a sharp tool SPL that can handle various complex Excel scenarios, and

The group and summary of data is a common problem encountered during work. For simple requirements such as summing, averaging, and counting, it can be achieved directly using Excel’s group and summary or pivot tables. However, when encountering more complex requirements, it is impossible or difficult to implement them, such as filtering and sorting the grouped data based on the summarized values or calculating the ranking within each group. Moreover, Excel’s group and summary operations are not flexible enough, such as how to copy and extract summary items and automatically update them; how to export each type of data after

When processing Excel data, there is an important requirement to filter and extract data that meets one’s own requirements. Of course, we can use Excel’s filtering function to filter and copy the data that meets the conditions. However, the Excel filtering function only filters out static values. When there are new or modified filtering criteria or source data, we need to constantly repeat the filtering and copying operation. Especially when the source data changes and cannot be automatically updated, it is easy to encounter the problem of referencing incorrect data. To solve this problem, Excel also has VLOOKUP available, but

Usually, a large amount of data preparation work is needed before performing data analytics and AI computing. It involves arranging different data sources and different types of data into a consistent format. As the real-world scenarios are extremely complicated and diverse, almost no visualization tools can do the job and generally programming is needed. Many free scripting languages are available for data preparation work in the related industries. Among them Python Pandas is preferred by users because of its supply of interfaces for various data sources and a rich library of computing functions. esProc SPL is an emerging data handling

Excel is currently the most widely used software tool in the workplace, with a large number of “Excelmen” in various industries using it to draw tables and perform calculations. It can be said that without Excel, many work staff cannot work properly. However, Excel is not perfect either. It basically lacks automatic processing capabilities, and its formula calculation ability is not strong enough, resulting in many daily tasks that can only be manually processed on Excel, with low efficiency. As a result, working overtime in Excel has become a common occurrence among many “Excelmen”. Let’s take a look at how

SQL is widely used, and data scientists (analysts) often need to use SQL to query and process data in their daily work. Many enterprises hold the view that as long as the IT department builds a data warehouse (data platform) and provides SQL, data scientists can freely query and analyze enterprise data.

SPL is designed primarily to address the difficulties of SQL (difficult to code and slow to run for complex task, difficult to perform cross-source calculation, dependent on stored procedure), and its application scenarios are similar to those of SQL.

In data analysis, it is inevitable to encounter large data files that cannot be loaded in memory. How to query and calculate large files? This paper analyzes and compares the advantages and disadvantages of several common methods, esProc SPL is the most suitable script for data analysts to process large files.Go to Looking for suitable tools for querying and calculating large files for more infomation.